scholarly journals Nonlinear Model Predictive Control for Suppressing Variations of Blade Bending Stress in Floating Offshore Wind Turbines Affected by Strong Winds

2018 ◽  
Vol 54 (2) ◽  
pp. 156-166 ◽  
Author(s):  
Kazuhiro UENO ◽  
Masaki YAMADA ◽  
Ken HANEDA ◽  
Toshiki CHUJO ◽  
Toshiyuki OHTSUKA
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Wind Turbines ◽  
Nonlinear Model Predictive Control ◽  
Offshore Wind ◽  
Bending Stress ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Strong Winds

Hybrid Model Predictive Control of Floating Offshore Wind Turbines with Artificial Muscle Actuated Mooring Lines

2022 ◽  
Author(s):  
Zhongyou Wu ◽  
Yaoyu Li
Keyword(s):  
Model Predictive Control ◽  
Hybrid Model ◽  
Predictive Control ◽  
Wind Turbines ◽  
Artificial Muscle ◽  
Offshore Wind ◽  
Half Cycle ◽  
Platform Motion ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines

Abstract Floating offshore wind turbines (FOWTs) are subject to undesirable platform motion and significant increase in fatigue loads compared to their onshore counterparts. We have recently proposed using the Fishing Line Artificial Muscle (FLAM) actuators to realize active mooring line force control (AMLFC) for platform stabilization and thus load reduction, which features compact design and no need for turbine redesign. However, as for the thermally activated FLAM actuators, a major control challenge lies in the asymmetric dynamics for the heating and the cooling half cycle of operation. In this paper, for a tension-leg platform (TLP) based FOWT with FLAM actuator based AMLFC, a hybrid dynamic model is obtained with platform pitch and roll degrees of freedom included. Then a hybrid model predictive control (HMPC) strategy is proposed for platform motion stabilization, with preview information on incoming wind and wave. A move blocking scheme is used to achieve reasonable computational efficiency. FAST based simulation study is performed using the NREL 5 MW wind turbine model. Under different combinations of wind speed, wave height and wind directions, simulation results show that the proposed control strategy can significantly reduce the platform roll and tower-base side-to-side bending moment, with mild level of actuator power consumption.

Nonlinear model predictive control of wind turbines using LIDAR

Wind Energy ◽  
2012 ◽  
Vol 16 (7) ◽  
pp. 1107-1129 ◽  
Author(s):  
David Schlipf ◽  
Dominik Johannes Schlipf ◽  
Martin Kühn
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Wind Turbines ◽  
Nonlinear Model Predictive Control
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